Smart Email Matching – Accelerating Load Discovery for Carriers

DAT Freight & Analytics | Lead UX Researcher

🔍 TL;DR

Role: Lead UX Researcher
Team: Product, Design, Engineering, Data Science, Product Marketing
Business Impact:

  • Created a new email feature for DAT One Web Carriers seeking loads

  • Achieved 50% adoption among carriers who emailed brokers (40% of the total carrier population in USA)

  • Reduced time to find loads by 30%

  • Improved carrier CSAT from 65% in Q4 2024 → 70% in Q1 2025
    My Contribution: Led discovery and insight strategy across 8 product teams, facilitated collaborative alignment, introduced AI tools to accelerate synthesis, and directly shaped feature prioritization and go-to-market strategy

🧭 The Challenge

During qualitative research with dispatchers, I observed consistent email-based broker outreach — a workaround that was inefficient and outside the platform. To validate scale, I turned to Mixpanel, where I discovered high outbound email activity from carriers.

This signaled a clear opportunity: support this behavior natively in DAT One Web. The challenge? Define a lightweight feature that improved carrier-broker communication without introducing friction — and build alignment across a cross-functional team that I wasn’t embedded in.

🤝 My Collaborative Process

1. Cross-Team Support, Not Embedded Execution
As Lead UX Researcher overseeing eight product teams, I wasn't embedded in this squad — but I joined their weekly design syncs to stay connected with Product, Design, Engineering, and Product Marketing.

To inform collaboration, I introduced Google Gemini to synthesize historical research across DAT. This enabled me to surface themes around communication friction and inform a collaborative workshop I facilitated using Mural and a previous insight deck. In that session, we:

  • Shared dispatcher pain points and behavior patterns

  • Mapped team assumptions, user journeys, and decision points

  • Co-created a shared research plan that guided feature development

2. Shared Ownership of Insights
Rather than holding findings until the end, I created insight checkpoints throughout the sprint:

  • Live synthesis during usability sessions

  • Insight huddles for real-time feedback

  • Early drafts of messaging reviewed jointly with Product Marketing

This made insights actionable and ensured stakeholders remained engaged in shaping direction.

3. Decisions, Not Deliverables
I focused on tools for alignment and action:

  • A decision matrix to prioritize email scenarios and the ability to build your own template

  • A friction-to-opportunity map that reshaped the MVP scope

  • Messaging recommendations using language directly from users

The team identified the feature as low-hanging fruit and quickly developed a prototype. We ran an A/B test in Optimizely with 50% of our carrier population, which showed 40% adoption. Based on the results, we rolled it into full production.

📈 Outcome & Impact

  • 50% adoption among carriers who email brokers (40% of the total carrier population in USA)

  • 30% faster load discovery for participating carriers

  • CSAT jump from 65% → 70% (Q4 2024 → Q1 2025)

  • Enabled faster iteration cycles and stronger go-to-market alignment

  • Demonstrated how research leadership — even without embedding — can drive product clarity and speed

💡 Reflections

This project underscored the power of proactive, cross-functional research leadership. Even without being embedded, I built trust and momentum through intentional facilitation, strategic tooling, and a shared sense of purpose. By introducing AI synthesis via Gemini, we accelerated learning, reduced redundancy, and gave the team confidence to ship fast — with measurable impact.

Here you can see a carrier clicking on an email of a broker to inquire about a load. In the old experience it would just link to your email address and allow you to email the broker. In the new experience, you can select from user friendly templates which you can tailor to your companies needs.